Estimating SARS-CoV-2 seroprevalence and epidemiological parameters with uncertainty from serological surveys

Larremore, Daniel B.; Fosdick, Bailey K.; Bubar, Kate M.; Zhang, Sam; Kissler, Stephen M; Metcalf, C. Jessica E.; Buckee, Caroline O.; Grad, Yonatan H.

doi:10.1101/2020.04.15.20067066

Cited by 58 publications

(79 citation statements)

References 41 publications

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“…The model incorporates transmission from both asymptomatic and presymptomatic 27 infectious people. By fitting the model to local epidemic dynamics (using daily reported COVID-19 deaths), 28 we can estimate key epidemiological metrics and evaluate the effectiveness of different long-term interven- 29 tion strategies. Specifically, we explore three classes of strategies: 1) long-term shelter-in-place orders, 30 which we consider the most drastic approach; 2) widespread testing and isolation of symptomatic people 31 paired with less intensive social distancing in the general population; 3) an adaptive triggering approach 32 2 .…”

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confidence: 99%

“…Improved testing coverage would also have the added benefit of: 1) improving implementa-163 tion of contact tracing to identify and quarantine contacts before they potentially become asymptomatic 164 and presymptomatic spreaders, and 2) helping to fit models and other public health surveillance tools to 165 COVID-19 cases, rather than deaths. 166 Recent evidence suggests that a large proportion of infected people may be asymptomatic or presymp-167 tomatic 25,26 , and that a larger proportion of the population than previously understood may have already 168 been infected (Stanford seroprevalence study: 27 ; Harvard seroprevalence study: 28 ). Our model currently…”

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confidence: 99%

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The impact of long-term non-pharmaceutical interventions on COVID-19 epidemic dynamics and control

Childs

Kain

Kirk

et al. 2020

Preprint

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Non-pharmaceutical interventions to combat COVID-19 transmission have worked to slow the spread of the epidemic but can have high socio-economic costs. It is critical we understand the efficacy of nonpharmaceutical interventions to choose a safe exit strategy. Many current models are not suitable for assessing exit strategies because they do not account for epidemic resurgence when social distancing ends prematurely (e.g., statistical curve fits) nor permit scenario exploration in specific locations. We developed an SEIR-type mechanistic epidemiological model of COVID-19 dynamics to explore temporally variable non-pharmaceutical interventions. We provide an interactive tool and code to estimate the transmission parameter, β, and the effective reproduction number, R E . We fit the model to Santa Clara County, California, where an early epidemic start date and early shelter-in-place orders could provide a model for other regions. As of April 22, 2020, we estimate an R E of 0.982 (95% CI: 0.849 -1.107) in Santa Clara County. After June 1 (the end-date for Santa Clara County shelter-in-place as of April 27), we estimate a shift to partial social distancing, combined with rigorous testing and isolation of symptomatic individuals, is a viable alternative to indefinitely maintaining shelter-in-place. We also estimate that if Santa Clara County had waited one week longer before issuing shelter-in-place orders, 95 additional people would have died by April 22 (95% CI: 7 -283). Given early life-saving shelter-in-place orders in Santa Clara County, longer-term moderate social distancing and testing and isolation of symptomatic individuals have the potential to contain the size and toll of the COVID-19 pandemic in Santa Clara County, and may be effective in other locations.

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confidence: 99%

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confidence: 99%

The impact of long-term non-pharmaceutical interventions on COVID-19 epidemic dynamics and control

Childs

Kain

Kirk

et al. 2020

Preprint

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“…This work as well as other similar studies that investigate the effect of test accuracy on estimating seroprevalence [12], highlight the necessity of integrating the development of serological tests with the design of the serosurveys, in which they will be applied. This is especially relevant during the current Coronavirus pandemic as the serological tests are developed at the same time as the serosurveys are being conducted.…”

Section: Discussionmentioning

confidence: 63%

“…An alternative way to correct for the sensitivity and specificity is described by Larremore et al (2020). They use a Bayesian approach that samples from a posterior distribution that includes the estimates of the sensitivity and specificity [12]. We also apply this correction to both the maximal Youden and the high specificity method.…”

Section: Methodsmentioning

confidence: 99%

“…Such a correction has recently been used in the estimation of the seroprevalence in the Coronavirus pandemic [11]. A Bayesian version of the correction has been proposed to infer age-stratified seroprevalences in the context of epidemiological transmission models [12]. However, the corrections work well only for high seroprevalence and relatively high specificity.…”

Section: Introductionmentioning

confidence: 99%

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Estimating cumulative incidence of SARS-CoV-2 with imperfect serological tests: exploiting cutoff-free approaches

Bouman

Riou

Bonhoeffer

et al. 2020

Preprint

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Large-scale serological testing in the population is essential to determine the true extent of the current Coronavirus pandemic. Serological tests measure antibody responses against pathogens and define cutoff levels that dichotomize the quantitative test measures into sero-positives and negatives. With the imperfect tests that are currently available to test for past SARS-CoV-2 infection, the fraction of seropositive individuals in serosurveys is a biased estimator of seroprevalence and is usually corrected post-hoc to account for the sensitivity and specificity. Here we use a likelihood-based inference method -previously called mixture models -for the estimation of the seroprevalence that does not require to define cutoffs by integrating the quantitative test measures directly into the statistical inference procedure. We confirm that this likelihood-based method outperforms the methods based on cutoffs and post-hoc corrections leading to less variation in point-estimates of the seroprevalence and its temporal trend. We illustrate how the likelihood-based method can be used to optimize the design of serosurveys with imperfect serological tests. We also provide guidance on the number of control and case sera that are required to quantify the test's ambiguity sufficiently to enable the reliable estimation of the seroprevalence. Lastly, we show how this approach can be used to identify classes of case sera with an unknown distribution of quantitative test measures that have not been used for test validation. An R-package with the likelihood and power analysis functions is provided. Our study advocates to using serological tests without cutoffs, especially if they are used to determine parameters characterizing populations rather than individuals. This approach circumvents some of the shortcomings of cutoff-based methods with post-hoc correction at exactly the low seroprevalence levels and test accuracies that we are currently facing in COVID-19 serosurveys. Author SummaryAs other pathogens, SARS-CoV-2 elicits antibody responses in infected people that can be detected in their blood serum as early as a week after the infection until long after recovery. The presence of SARS-CoV-2 specific antibodies can therefore be used as a marker of past infection, and the prevalence of seropositive people, i.e. people with specific antibodies, is a key measure to determine the extent of the Coronavirus pandemic. The serological tests, however, are usually not perfect, yielding false positive and negative results.Here we exploit an approach that refrains from classifying people as seropositive or negative, but rather compares the antibody level to that of confirmed cases and controls. This approach leads to more reliable seroprevalence estimates, especially for the low prevalence and low test accuracies that we face during the current Coronavirus pandemic. We also show how this approach can be extended to infer the presence of cases that have not been used for validating the test, such as people that underwent a mild or even asym...

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Dynamics of behavior change in the COVID world

Moya

Peniche

Kline

et al. 2020

American J Hum Biol

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Estimating SARS-CoV-2 seroprevalence and epidemiological parameters with uncertainty from serological surveys

Cited by 58 publications

References 41 publications

The impact of long-term non-pharmaceutical interventions on COVID-19 epidemic dynamics and control

The impact of long-term non-pharmaceutical interventions on COVID-19 epidemic dynamics and control

Estimating cumulative incidence of SARS-CoV-2 with imperfect serological tests: exploiting cutoff-free approaches

Dynamics of behavior change in the COVID world

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